Detail publikace

Enhancing Perimeter Protection using Φ-OTDR and CNN for Event Classification

TOMAŠOV, A. ZÁVIŠKA, P. SPURNÝ, V. DEJDAR, P. MÜNSTER, P. HORVÁTH, T. KLÍČNÍK, O.

Originální název

Enhancing Perimeter Protection using Φ-OTDR and CNN for Event Classification

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The paper introduces an enhanced method combining Φ-OTDR and CNNs for an accurate object classification for perimeter protection. The proposed approach achieves an accuracy of 91 % of common events in the optical fiber vicinity.

Klíčová slova

Convolutional Neural Networks;Distributed Acoustic Sensing;Event Classification;Perimeter Protection;Phase-sensitive Optical Time-Domain Reflectometry

Autoři

TOMAŠOV, A.; ZÁVIŠKA, P.; SPURNÝ, V.; DEJDAR, P.; MÜNSTER, P.; HORVÁTH, T.; KLÍČNÍK, O.

Vydáno

16. 2. 2024

Místo

Hamamatsu, Japan

ISBN

978-1-957171-30-2

Kniha

In Prociideings of 28th International Conference on Optical Fiber Sensors

Strany počet

4

URL

https://opg.optica.org/abstract.cfm?uri=OFS-2023-W4.39

BibTex

@inproceedings{BUT185620,
  author="Adrián {Tomašov} and Pavel {Záviška} and Vladimír {Spurný} and Petr {Dejdar} and Petr {Münster} and Tomáš {Horváth} and Ondřej {Klíčník}",
  title="Enhancing Perimeter Protection using Φ-OTDR and CNN for Event Classification",
  booktitle="In Prociideings of 28th International Conference on Optical Fiber Sensors",
  year="2024",
  pages="4",
  address="Hamamatsu, Japan",
  doi="10.1364/OFS.2023.W4.39",
  isbn="978-1-957171-30-2",
  url="https://opg.optica.org/abstract.cfm?uri=OFS-2023-W4.39"
}